While vehicles have traditionally been thought of as purely mechanical, they are certainly not immune from digital transformation, as we are seeing through the growth of new technologies. The results that have been achieved in the fields of AI, machine learning, and big data analytics are transforming the auto industry.

For Original Equipment Manufacturers (OEMs), digital enhancements are now the inevitable solution as they make continual investments in improving the quality of the engines, chassis and other parts, focused on safety and productivity. With these technologies, OEMs are improving the driving experience to meet customer expectations – and are now in the business of designing and building the Digital Vehicle or Digital Car.

With network connectivity and quality reaching the far corners of the world, the ubiquity of smartphones, as well as the emergence of Internet of Things, the transportation industry is on the verge of major transformation. Major technology players along with auto manufacturers are taking note. In a 2015 interview, Apple CEO Tim Cook stated that the auto industry is in for a “massive change” with software becoming “an increasingly important part of the car of the future.” Connected cars are a key result of this industry disruption, and will become mainstream globally by 2025.

Vehicle recalls are a top priority for digital transformation

Recalling faulty products is a difficult task in any industry, and vehicle recalls and withdrawals impact many Auto OEMs every year. If managed poorly, a recall can have devastating consequences with serious implications for companies of all sizes. Controls in the automotive industry are of the utmost importance, as the fallout goes further than a company’s reputation, market share, and bottom line. Beyond financial and reputational damage, people can get seriously hurt as a result of product failures.

Recent research conducted by Auto Express has brought some disturbing news to light. The figures obtained from the Driver Vehicle Standards Agency (DVSA) demonstrate the gloomy state of affairs for the automotive industry: roughly 2.2 million vehicles were affected by recalls, with the top 10 list of recalls since 2012 led by Takata Corporation (an automotive parts company based in Japan recently involved in a wide scale airbag recall). What makes the situation worse is that just 47.7 percent of car owners went back to dealers for repairs. That’s a lot of dangerous, faulty vehicles still on the road.

In June 2007, one major Auto OEM was forced to recall more than 400,000 vehicles over safety issues, affecting vehicles that were built in the company’s one plant. Problems included loss of motive power while driving, or unintended movement when the parking brake is applied, presenting obvious safety concerns for drivers. And this is not the only case. A South Korean OEM recently recalled over 240,000 vehicles due to defects in parking brake warning lights.

This area could seriously benefit from digital improvements. Recalls are complex and have serious consequences if mishandled. The initiation of a recall is no time for an introduction to the many logistical and compliance challenges at play. Numerous supply chain partners and some regulators now require manufacturers to have extensive recall plans ready to launch at a moment’s notice. With the proper systems and technologies in place, a recall event can be effectively managed to mitigate financial and legal risk, increase customer loyalty, and prevent lasting damage to vehicle brands.

Digital cars = better information = better recalls

The biggest benefit of connected cars to the recall process is the unprecedented levels of data they can provide. We are in the fourth industrial revolution (Industry 4.0), in which smart and connected devices powered by machine learning and AI are able to predict faults and anomalies in the manufacturing process. With the recent explosion of data and the increasing volume of sensors on everyday devices, these technologies that have been around for decades are now becoming ubiquitous.

Imagine being able to predict something going wrong before it actually does, to proactively take corrective action and prevent failures before they happen. When it comes to safety issues, the sooner they are discovered, the better – and advanced data analysis can help identify the early warning signs. Using multiple databases, complaints can be tracked and researched to pinpoint patterns in specific parts’ performance.

This is where AI and machine learning come into play. These technologies can help automotive manufacturers reduce recalls and improve driver safety by making sense of troves of data, testing potential problems with the use of ‘digital twins’ to run more precise and targeted simulations. These are granular virtual copies of parts in the manufacturing process powered by deep learning and artificial intelligence. In testing, they can garner insights that address the tiniest of issues, which would otherwise be missed during a manual inspection process.

By analysing the flood of manufacturing data received by machines thoroughly and looking for anomalies via machine learning, you are able to predict catastrophic failures earlier, avoiding total breakdowns and saving businesses from huge losses in revenue and brand equity. This in turn minimises the need for businesses to issue recalls routinely, or for consumers to suffer the potentially dangerous fallout from faulty equipment.

Better recalls = better reputation = better business

Speeding up investigations and the development of safety solutions means that automakers can in turn perform outreach to vehicle owners more effectively. Accurate owner information is what drives every step in the auto recall process. With enhanced data, the right customers are notified, repairs can be appropriately tracked, and compliance and regulatory reporting can be offered with the utmost confidence.

An effective recall not only keeps lawsuits and competitors at bay, it fosters the goodwill needed to maintain strong brand equity. It’s not the recall itself that differentiates a brand, but rather how well it is handled. When outreach is enhanced by data, it in turn enhances customer loyalty and drives better business outcomes.